Are Antiplatelet Agents Beneficial in Essential Thrombocythemia? Maybe Yes, Probably No
Bibliographic record
Abstract
Editorials1 August 2017Are Antiplatelet Agents Beneficial in Essential Thrombocythemia? Maybe Yes, Probably NoJoel S. Bennett, MDJoel S. Bennett, MDFrom Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M17-1378 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Thrombocytosis, which is frequently encountered in clinical practice, is usually secondary to infection, inflammation, tumor, surgical stress, iron deficiency, acute blood loss, or splenectomy (1). In rare instances, it is a primary process, most often a manifestation of the myeloproliferative disorders essential thrombocythemia (ET), polycythemia vera (PV), or primary myelofibrosis (PMF) (2). It is important to differentiate primary from secondary thrombocytosis. The clinical course of myeloproliferative disorders can be punctuated by thrombotic events as well as hemorrhage, and both ET and PV can evolve into myelofibrosis or acute leukemia. In contrast, untoward symptoms due to thrombocytosis are sufficiently unusual in ...References1. Sulai NH, Tefferi A. Why does my patient have thrombocytosis? Hematol Oncol Clin North Am. 2012;26:285-301, viii. [PMID: 22463828] doi:10.1016/j.hoc.2012.01.003 CrossrefMedlineGoogle Scholar2. Spivak JL. Myeloproliferative neoplasms. N Engl J Med. 2017;376:2168-2181. [PMID: 28564565] doi:10.1056/NEJMra1406186 CrossrefMedlineGoogle Scholar3. Cazzola M, Kralovics R. From Janus kinase 2 to calreticulin: the clinically relevant genomic landscape of myeloproliferative neoplasms. Blood. 2014;123:3714-9. [PMID: 24786775] doi:10.1182/blood-2014-03-530865 CrossrefMedlineGoogle Scholar4. Rumi E, Pietra D, Pascutto C, Guglielmelli P, Martínez-Trillos A, Casetti I, et al; Associazione Italiana per la Ricerca sul Cancro Gruppo Italiano Malattie Mieloproliferative Investigators. Clinical effect of driver mutations of JAK2, CALR, or MPL in primary myelofibrosis. Blood. 2014;124:1062-9. [PMID: 24986690] doi:10.1182/blood-2014-05-578435 CrossrefMedlineGoogle Scholar5. Papadakis E, Hoffman R, Brenner B. Thrombohemorrhagic complications of myeloproliferative disorders. Blood Rev. 2010;24:227-32. [PMID: 20817333] doi:10.1016/j.blre.2010.08.002 CrossrefMedlineGoogle Scholar6. Carobbio A, Thiele J, Passamonti F, Rumi E, Ruggeri M, Rodeghiero F, et al. Risk factors for arterial and venous thrombosis in WHO-defined essential thrombocythemia: an international study of 891 patients. Blood. 2011;117:5857-9. [PMID: 21490340] doi:10.1182/blood-2011-02-339002 CrossrefMedlineGoogle Scholar7. Campbell PJ, MacLean C, Beer PA, Buck G, Wheatley K, Kiladjian JJ, et al. Correlation of blood counts with vascular complications in essential thrombocythemia: analysis of the prospective PT1 cohort. Blood. 2012;120:1409-11. [PMID: 22709688] doi:10.1182/blood-2012-04-424911 CrossrefMedlineGoogle Scholar8. Tefferi A, Barbui T. Essential thrombocythemia and polycythemia vera: focus on clinical practice. Mayo Clin Proc. 2015;90:1283-93. [PMID: 26355403] doi:10.1016/j.mayocp.2015.05.014 CrossrefMedlineGoogle Scholar9. Landolfi R, Marchioli R, Kutti J, Gisslinger H, Tognoni G, Patrono C, et al; European Collaboration on Low-Dose Aspirin in Polycythemia Vera Investigators. Efficacy and safety of low-dose aspirin in polycythemia vera. N Engl J Med. 2004;350:114-24. [PMID: 14711910] CrossrefMedlineGoogle Scholar10. Chu DK, Hillis CM, Leong DP, Anand SS, Siegal DM. Benefits and risks of antithrombotic therapy in essential thrombocythemia. A systematic review. Ann Intern Med. 2017;167:170-80. doi:10.7326/M17-0284 LinkGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.Disclosures: The author has disclosed no conflicts of interest. The form can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M17-1378.Corresponding Author: Joel S. Bennett, MD, Hematology-Oncology Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Room 814, BRB II/III, 421 Curie Boulevard, Philadelphia, PA 19104; e-mail, [email protected]med.upenn.edu.This article was published at Annals.org on 27 June 2017. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoBenefits and Risks of Antithrombotic Therapy in Essential Thrombocythemia Derek K. Chu , Christopher M. Hillis , Darryl P. Leong , Sonia S. Anand , and Deborah M. Siegal Metrics Cited byAntiplatelet use in patients with essential thrombocythemia: A survey of opinion and Canadian practice 1 August 2017Volume 167, Issue 3Page: 206-207KeywordsAntiplatelet therapyAspirinHemorrhageMyeloproliferative disordersPlateletsPolycythemia veraRelative riskSystematic reviewsThrombocytosisThrombosis ePublished: 27 June 2017 Issue Published: 1 August 2017 Copyright & PermissionsCopyright © 2017 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".